Improving Mobile Reading Experiences While Walking Through Automatic Adaptations and Prompted Customization

Increasingly more people are consuming information on the go, and yet walking can significantly affect the ability to read text documents on mobile devices. In this work, we propose a system that automatically detects when a user is walking while reading on mobile devices to suggest automatic adaptations and recommendations to improve reading experiences. The user can also customize these suggested adaptations in real time, which our system uses to offer future recommendations. We ran a preliminary user study to evaluate our prototype and identify challenges and opportunities of mixed-initiative adaptations for reading on the go.